Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- DTU Electro
- AALTO UNIVERSITY
- ; Swansea University
- AMOLF
- Aalborg University
- Curtin University
- DAAD
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); Delft
- Delft University of Technology (TU Delft); yesterday published
- Leibniz
- NTNU Norwegian University of Science and Technology
- Swansea University;
- The University of Manchester;
- University of Florida
- University of Groningen
- University of Newcastle
- Vrije Universiteit Brussel
- Wetsus - European centre of excellence for sustainable water technology
- 9 more »
- « less
-
Field
-
, these models often use simplified, linearized assumptions, limiting their capacity to capture the nonlinear complexities inherent in real-world hydrological processes. Recently, there has also been the branch
-
scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive
-
to: - Developing underwater communication systems using deep learning which are well-performing to nonlinear channels. - Establishing a deep learning architecture which is optimal for underwater acoustic
-
aspects include rough paths and subsequent developments for nonlinear stochastic partial differential equations. The theory of signatures and rough volatility also provides important connections to algebra